Working Paper Series
Missing Variables and Two-Stage Least-Squares Estimation from More than One Data Set
Abstract: In a situation when no single sample inc1udes all the
endogenous variables of a simultaneous equation model but there are two (or
more) non-overlapping samples and each variable is included in at least
one, then it is possible to pool the data and estimate the model
consistently by a two-stage least-squares procedure. The asymptotic
variances of the estimates are not always larger than those which would
have been obtained with TSLS from one complete sample. It is also shown
that under certain assumptions the same approach can be applied to an
ordinary regression model.
Keywords: TLSL; Statistical modeling; (follow links to similar papers)
JEL-Codes: C10; (follow links to similar papers)
19 pages, April 1982
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